{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:OTJDXGUIQOWOXABZGSMX4WVR5B","short_pith_number":"pith:OTJDXGUI","canonical_record":{"source":{"id":"2310.02279","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"title_canon_sha256":"7db72a01efbaa8f094beb84903b0741533eade5265cc1ef329bf7cd4ffcaf839","abstract_canon_sha256":"5c019c832956e7b302324e3a33c180889d560bc68bd34ae14a3548e76440a5fc"},"schema_version":"1.0"},"canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","source":{"kind":"arxiv","id":"2310.02279","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.02279","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"arxiv_version","alias_value":"2310.02279v3","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.02279","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_12","alias_value":"OTJDXGUIQOWO","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_16","alias_value":"OTJDXGUIQOWOXABZ","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_8","alias_value":"OTJDXGUI","created_at":"2026-07-05T08:02:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:OTJDXGUIQOWOXABZGSMX4WVR5B","target":"record","payload":{"canonical_record":{"source":{"id":"2310.02279","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"title_canon_sha256":"7db72a01efbaa8f094beb84903b0741533eade5265cc1ef329bf7cd4ffcaf839","abstract_canon_sha256":"5c019c832956e7b302324e3a33c180889d560bc68bd34ae14a3548e76440a5fc"},"schema_version":"1.0"},"canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:02:21.772748Z","signature_b64":"HW6Oiv56zGWrScig3L2vSflBPUdU640Y/tGSKTXKNULVkVTx+EL2n5xm5lTHfAhBX3c9e2AEsGjLAiOpSQbTBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","last_reissued_at":"2026-07-05T08:02:21.772187Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:02:21.772187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.02279","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:02:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BDcyN47dyTZj1SCmeHO7kqUnx2lEDFNQwGQXFQFrWI7xwX6i1/1V1jJfUE6EV21Bxtwnh2INE+1+9nXaKM6BBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T12:52:00.051397Z"},"content_sha256":"17fb0f32f65240eb8f6106ff87bec874efe70b559876859322c20a8b33f84778","schema_version":"1.0","event_id":"sha256:17fb0f32f65240eb8f6106ff87bec874efe70b559876859322c20a8b33f84778"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:OTJDXGUIQOWOXABZGSMX4WVR5B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Stefano Ermon, Toshimitsu Uesaka, Wei-Hsiang Liao, Yuhta Takida, Yuki Mitsufuji, Yutong He","submitted_at":"2023-10-01T05:07:17Z","abstract_excerpt":"Consistency Models (CM) (Song et al., 2023) accelerate score-based diffusion model sampling at the cost of sample quality but lack a natural way to trade-off quality for speed. To address this limitation, we propose Consistency Trajectory Model (CTM), a generalization encompassing CM and score-based models as special cases. CTM trains a single neural network that can -- in a single forward pass -- output scores (i.e., gradients of log-density) and enables unrestricted traversal between any initial and final time along the Probability Flow Ordinary Differential Equation (ODE) in a diffusion pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.02279","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2310.02279/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:02:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JLqaC5lYzM96tfbY1vQbNqCAZdVoWDyrgryahZQmgzrNoPrYC4OHJkLanGxeYyDCWDeuEZiqNcIXpICnQUz0DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T12:52:00.051769Z"},"content_sha256":"1e1fa0e6a5b857bfb270abfae660f6a8b604cea49ddc08936dc53cbc0377acb1","schema_version":"1.0","event_id":"sha256:1e1fa0e6a5b857bfb270abfae660f6a8b604cea49ddc08936dc53cbc0377acb1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OTJDXGUIQOWOXABZGSMX4WVR5B/bundle.json","state_url":"https://pith.science/pith/OTJDXGUIQOWOXABZGSMX4WVR5B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OTJDXGUIQOWOXABZGSMX4WVR5B/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T12:52:00Z","links":{"resolver":"https://pith.science/pith/OTJDXGUIQOWOXABZGSMX4WVR5B","bundle":"https://pith.science/pith/OTJDXGUIQOWOXABZGSMX4WVR5B/bundle.json","state":"https://pith.science/pith/OTJDXGUIQOWOXABZGSMX4WVR5B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OTJDXGUIQOWOXABZGSMX4WVR5B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:OTJDXGUIQOWOXABZGSMX4WVR5B","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"5c019c832956e7b302324e3a33c180889d560bc68bd34ae14a3548e76440a5fc","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","title_canon_sha256":"7db72a01efbaa8f094beb84903b0741533eade5265cc1ef329bf7cd4ffcaf839"},"schema_version":"1.0","source":{"id":"2310.02279","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.02279","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"arxiv_version","alias_value":"2310.02279v3","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.02279","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_12","alias_value":"OTJDXGUIQOWO","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_16","alias_value":"OTJDXGUIQOWOXABZ","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_8","alias_value":"OTJDXGUI","created_at":"2026-07-05T08:02:21Z"}],"graph_snapshots":[{"event_id":"sha256:1e1fa0e6a5b857bfb270abfae660f6a8b604cea49ddc08936dc53cbc0377acb1","target":"graph","created_at":"2026-07-05T08:02:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2310.02279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Consistency Models (CM) (Song et al., 2023) accelerate score-based diffusion model sampling at the cost of sample quality but lack a natural way to trade-off quality for speed. To address this limitation, we propose Consistency Trajectory Model (CTM), a generalization encompassing CM and score-based models as special cases. CTM trains a single neural network that can -- in a single forward pass -- output scores (i.e., gradients of log-density) and enables unrestricted traversal between any initial and final time along the Probability Flow Ordinary Differential Equation (ODE) in a diffusion pro","authors_text":"Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Stefano Ermon, Toshimitsu Uesaka, Wei-Hsiang Liao, Yuhta Takida, Yuki Mitsufuji, Yutong He","cross_cats":["cs.AI","cs.CV","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","title":"Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.02279","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:17fb0f32f65240eb8f6106ff87bec874efe70b559876859322c20a8b33f84778","target":"record","created_at":"2026-07-05T08:02:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"5c019c832956e7b302324e3a33c180889d560bc68bd34ae14a3548e76440a5fc","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","title_canon_sha256":"7db72a01efbaa8f094beb84903b0741533eade5265cc1ef329bf7cd4ffcaf839"},"schema_version":"1.0","source":{"id":"2310.02279","kind":"arxiv","version":3}},"canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","first_computed_at":"2026-07-05T08:02:21.772187Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:21.772187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HW6Oiv56zGWrScig3L2vSflBPUdU640Y/tGSKTXKNULVkVTx+EL2n5xm5lTHfAhBX3c9e2AEsGjLAiOpSQbTBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:21.772748Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.02279","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17fb0f32f65240eb8f6106ff87bec874efe70b559876859322c20a8b33f84778","sha256:1e1fa0e6a5b857bfb270abfae660f6a8b604cea49ddc08936dc53cbc0377acb1"],"state_sha256":"0f7c2bab1fd354527fe2ec95ac54abd8a2a152a8cb35635ac29cd695d953c2bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M+hKCAzybi9/hI0MBcoUSRbSlwDVQAEdQP7QU014i3AKlaa9wCieFUtRQlTsJDoesprNLS/twKa7tgxGftm1AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T12:52:00.053685Z","bundle_sha256":"7e7942698cfa43e82274938d4ba609ee67b6e8249050ff79d19ef002dbc83374"}}